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What is Predictive Trend Analytics and is it Helpful to Businesses?

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Artificial Intelligence, Internet of Things and Machine Learning are the current face of technology. In fact, there are numerous AI-powered devices, robots and algorithms to make our work easier. AI has penetrated into almost all the domains – be it health sector, education or business. However, the question remains, ‘how do machines interact with each other or take decisions?’ Well, the answer to this is simple – they follow patterns based on their previous history i.e they start predicting the outcome vis-à-vis the situation. 

In this article, we will cover what predictive trend analytics is, how it impacts your marketing strategy and, in turn, your business. 

What is Predictive Trend Analytics: 

Predictive Trend Analytics in simple words is using historical data to predict and plan for the future outcome. In fact, predictive trend analytics is a subset of business intelligence. Essentially, machine learning and artificial intelligence-based tools help track a customer’s preferences or predict the demands of a certain product or service. This data is later used to advertise personalised customer content to increase conversion count. 

So, is the process of predictive trend analytics as simple as it sounds or is there more to it? Well, the answer is, yes there are a lot of complex processes that determine which prediction is the most accurate one. Let us move on to understand how predictive analytics works.


Working of Predictive Trend Analytics

To understand, let us take, for example, of Netflix. Netflix is the most used application for movies and series. However, have you ever wondered how Netflix knew what should you watch next after you’ve just finished watching a movie or series, then here is your answer! Netflix is a major data-driven company that analyses user behaviour to the maximum.

For instance, when did you watch the movie, did you complete it? If not, at what point did you leave it midway, did you return to it again, the ratings that are given, the scrolling and browsing behaviour and much more. Using several algorithms and data analysis, Netflix is able to predict the most suitable shows/movies you would prefer watching. 


Another common example that you may have come across is Amazon’s Suggestions when you purchase a product. Not only does Amazon suggest what you should purchase to complete the look but even goes further and tells you what other customers viewed based on your search query. Amazon is able to give such a prediction based on the historical data it stores. For this, it uses a No SQL database.


Amazon’s suggestions based on your search

Whether you’re a retailer or a manufacturer, irrespective of your business, you can implement this process. Say you’re an e-commerce retailer you can track your customer’s purchase patterns to predict if they are to come back again for a purchase or not. Or if they don’t complete the purchase, why did they abandon the cart and how many abandoned the same product. This analysis will help you predict not only the customer’s behaviour but also the product. On the other hand, if you’re a manufacturer of smart devices, you can track and monitor the usage of the device and collect the information. This information can then be used to analyse user behaviour which, in turn, can be used to market similar products or premium services to your customers. 

Depending on your business type viz. SMB or Enterprise, there are various  marketinh automation tools that you can enable to collect data from how and when the customer interacted with your website to predict their next move. HubSpot, Marketo, Act-On are some tools that you can use.


Advantages of Predictive Trend Analytics

Moving on, let us cover the 3 major advantages of enabling predictive trend analytics.


  1. Improves Performance Efficiency 

Predictive Trend Analytics enables you to tap into customer behaviour based on their usage of your product or purchase. This can help you to reduce abandon cart issues, as well as, help you gain a competitive advantage. Eventually, this helps in improving both the performance of the customer’s buyer journey and your business.


  2. Better Marketing Campaigns 

You might have run multiple marketing campaigns, some of them performing exceptionally well while there might be few that didn’t. Analysing your customer’s interaction on your website can help you predict how your customers will act. Moreover, it can also help upsell, cross-sell, and improve your revenue.


  3. Enhance Customer Experience 

A satisfied customer is most likely to return to your website as opposed to a customer who felt that the experience could have been better. Analysing customer behaviour helps you predict ‘if they will open your email’ or ‘which product they are likely to search’. This helps you to cater to them in a personalised manner, giving the feeling that the discount or products are custom-made especially for them (which is true). 




Predictive Trend Analytics is a fast and efficient way to gain insight into customers based on their shopping patterns and behaviour. Moreover, it helps you leverage and upscale your business website to suit the needs of your customers based on educative guesses. Have you implemented predictive analysis? If yes, how is your experience? Do let us know in the comments section below.

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